Optimization of optical lens-controlled scanning electron microscopic resolution using generalized regression neural network and genetic algorithm

A scanning electron microscope (SEM) is a sophisticated equipment employed for fine imaging of a variety of surfaces. In this study, prediction models of SEM were constructed by using a generalized regression neural network (GRNN) and genetic algorithm (GA). The SEM components examined include condenser lens 1 and 2 and objective lens (coarse and fine) referred to as CL1, CL2, OL-Coarse, and OL-Fine. For a systematic modeling of SEM resolution (R), a face-centered Box–Wilson experiment was conducted. Two sets of data were collected with or without the adjustment of magnification. Root-mean-squared prediction error of optimized GRNN models are GA 0.481 and 1.96×10^-12 for non-adjusted and adjusted data, respectively. The optimized models demonstrated a much improved prediction over statistical regression models. The optimized models were used to optimize parameters particularly under best tuned SEM environment. For the variations in CL2 and OL-Coarse, the highest R could be achieved at all conditions except a larger CL2 either at smaller or larger OL-Coarse. For the variations in CL1 and CL2, the highest R was obtained at all conditions but larger CL2 and smaller CL1.     

Organic wavelength‐converting‐film‐based hybrid planar white light‐emitting diodes

Abstract— In this study, organic wavelength‐converting films (WCFs) applied to InGaN blue LED‐based hybrid planar WLED has been fabricated. The organic dye layer in the WCF was formed between the upper and bottom polymer sheets by using a simple roll‐laminating technique. Subsequently, the hybrid planar WLEDs have been fabricated based upon these films. The luminous efficiency of green WCF‐based hybrid planar WLEDs with a single blue LED chip was 34.6 lm/W and that of red‐WCF‐assisted green WCF‐based hybrid planar WLEDs was 27.3 lm/W under 20 mA. The use of WCF to fabricate hybrid planar WLEDs showed better stability than that of directly coating organic color‐convergence materials (CCMs) on the LED chips. It only decreased to about 10% of the initial wavelength‐converting intensity after 1 hour of continual operation at 20 mA.     

Frictional properties of VA‐mode alignment‐film surfaces studied by frictional force microscopy

Abstract— The surface‐friction characteristics of the post‐bake temperature were compared to that of the rubbing condition on VA‐mode alignment films (AFs) using frictional force microscopy (FFM). The surface roughness and the surface frictional force increased when the temperature was elevated. However, the frictional asymmetry could not be detected by the frictional loop due to the instability of the side‐chain molecular arrangement. For the inter‐influences of the total friction and surface roughness, the density of the side chain was changed and it was intentionally rubbed for evaluation. The results showed that the total friction was higher when the rubbing was stronger and side‐chain density lower, and the surface roughness also increased in the same manner. This can be explained by the potential interaction due to the curved structure of the side‐chain surface that establishes the probe that is scanned and the top surface layer. In order to confirm the influence of the pre‐tilt angle on the tilt of the side chain, a test cell was produced under the same conditions and evaluated. The results showed that the pre‐tilt‐angle decreased according to the difference in density of the side chain and strength of rubbing after injecting liquid‐crystal (LC).     

An adaptive peer-to-peer live streaming system with incentives for resilience

Recently, there have been a lot of research efforts on peer-to-peer (P2P) live streaming services. P2P systems can be easily deployed since a participating peer’s resources (i.e., upload link bandwidth) can be exploited to distribute contents. However, how to adapt to leaving peers and how to encourage peers to contribute resources voluntarily are still challenging issues. In this paper, we propose Climber, an adaptive P2P live streaming system with incentives for resilience. Climber is based on the hybrid structure of a tree and a mesh, so as to achieve self-improvement and adaptation to users’ dynamic joining and leaving. Moreover, Climber substantiates an incentive mechanism that provides better resilience for peers with more upload bandwidth allocated. Simulation results reveal that Climber significantly reduces the topology maintenance cost compared to SplitStream and NICE-PRM. Also, simulation and analytical results verify that Climber can bound the level of disruption by dynamically adapting to the user churning rate.     

The moderating effects of psychological reactance and product involvement on online shopping recommendation mechanisms based on a causal map

The use of the Internet in the daily activities of individuals and firms has become entrenched, and online shopping has become commonplace. However, debates about how online shopping recommendation mechanisms (OREMs) should be designed have not been completely resolved. The challenge with traditional online shopping recommendation mechanisms (TR-OREMs) is that they focus too much on quantitative factors. Thus, they ignore causal interrelationships with qualitative factors that are believed to significantly impact quantitative factors. Considering only quantitative factors and ignoring qualitative ones likely distorts the final recommendation results. Another problem with TR-OREMs is that they ignore the perceived psychological reactance of consumers against the recommended products. Such consumer reactance may be reduced when the causal interrelationships among all the quantitative and qualitative factors are analyzed and incorporated properly into the OREM. To overcome these problems, we propose a causal map – online shopping recommendation mechanisms (CM-OREMs) based on a causal map. We analyzed possible causal relationships among quantitative and qualitative factors and incorporated them in the recommendation process to reduce consumer reactance against the recommendation results. Furthermore, an elaboration likelihood model (ELM) was used to build hypotheses about how the online shopping behavior of consumers is affected by OREMs based on the proposed causal map. Specifically, the performance of the proposed OREM was empirically analyzed by gathering experiment data from qualified respondents who were asked to refer to the proposed OREM before making purchasing decisions via mobile phones. Statistical results showed that the proposed OREMs could enhance consumer decision satisfaction, decision confidence, and attitude toward the recommended products. It could also positively affect consumer purchasing intentions. The OREM had a greater effect on the high-reactance group of participants than on the low-reactance group as well as on a high-involvement product versus a low-involvement product.     

Investigating factors that influence social presence and learning outcomes in distance higher education

There are many factors that influence distance learning especially in higher education where collaborative and communicative discourse is necessary for pursuing knowledge. Social presence, among other factors, is an important concept to be facilitated, developed and sustained in distance higher education as it promotes and supports discourse based learning. This study examines the relationship among demographic and other variables, social presence and learning satisfaction. Results showed demographic variables, such as gender, online learning experience and work status were not significant factors in terms of influencing on either social presence or learning satisfaction. While media integration and instructor’s quality teaching were significant predictors of both social presence and learning satisfaction, interactivity among participants was a predictor of social presence but not of learning satisfaction. Along with the study findings, some implications were discussed for online learning practitioners in higher education setting.     

A forward-secure e-mail protocol without certificated public keys

Forward secrecy in an e-mail system means that compromising of the long-term secret keys of the mail users and mail servers does not affect the confidentiality of the e-mail messages. Previous forward-secure e-mail protocols used the certified public keys of the users using PKI (Public Key Infrastructure). In this paper, we propose a password-based authenticated e-mail protocol providing forward secrecy. The proposed protocol does not require certified public keys and is sufficiently efficient to be executed on resource-restricted mobile devices.     

A modified advancing layers mesh generation for thin three-dimensional objects with variable thickness

A method of generating modified advancing layers mesh is proposed. In this paper the mesh generation process of semi-unstructured prismatic/tetrahedral mesh is presented for relatively thin three-dimensional geometries with variable thickness, as in the case of injection molding analysis. Prismatic meshes are generated by offsetting initial surface triangular meshes. During the mesh generation process, mesh quality is efficiently improved with the use of a new node relocation method. Finally, tetrahedral meshes are automatically generated in the rest of the domain. The mesh generating capability of the proposed algorithm is demonstrated with the several practical test cases.     

A remote user authentication scheme without using smart cards

User authentication is one of the fundamental procedures to ensure secure communications over an insecure public network channel. Especially, due to tamper-resistance and convenience in managing a password file, various user authentication schemes using smart cards have been proposed. A smart card however far from ubiquitous because of the high cost of a smart card and the infrastructure requirements. In this paper, we study secure user authentication using only a common storage device such as a universal serial bus (USB) memory, instead of using smart cards. We first show that the existing schemes using smart cards cannot be immediately converted into schemes using a common storage device. We then propose a practical and secure user authentication scheme, capable of supporting the use of the common storage device, which retains all the advantages of schemes using smart cards.     

Situation reactive approach to Vendor Managed Inventory problem

In this research, we deal with VMI (Vendor Managed Inventory) problem where one supplier is responsible for managing a retailer’s inventory under unstable customer demand situation. To cope with the nonstationary demand situation, we develop a retrospective action-reward learning model, a kind of reinforcement learning techniques, which is faster in learning than conventional action-reward learning and more suitable to apply to the control domain where rewards for actions vary over time. The learning model enables the inventory control to become situation reactive in the sense that replenishment quantity for the retailer is automatically adjusted at each period by adapting to the change in customer demand. The replenishment quantity is a function of compensation factor that has an effect of increasing or decreasing the replenishment amount. At each replenishment period, a cost-minimizing compensation factor value is chosen in the candidate set. A simulation based experiment gave us encouraging results for the new approach.